Objective

The last decades witnessed the ever growing effectiveness of Europe-subsidized border protection projects like SIVE and SIVICC. As maritime smuggling from Morocco towards the European borders of Portugal and Spain was combatted more effectively, the criminal modus operandi changed drastically, approaching air routes with cheap and small planes. New drone technology opens opportunity to both manned and unmanned airborne drug transports. Launched from any location and moving at low altitude and speed to mask their presence with the present clutter environment, drones can autonomously reach any landing site under nearly all circumstances.The ALFA system bridges this detection capability gap by drastically improving the situational awareness through the detection of LSS (Low, Small and Slow) manned and unmanned aircraft. ALFA is future-ready as technologies for drone detection will be a part of the system, which will use heterogeneous, easy-to-deploy mobile sensors based on several novel technologies. All sensor data, augmented by other existing sources of information, will be combined using evolved data fusion, providing accurate positional data for targets including eventual indication of the air vehicle type and reliable prediction of its landing site. This information will be communicated to the regional law enforcement units using a secure communication link and mobile device application, drastically improving the reaction time.Final ALFA capabilities will be demonstrated in a realistic operational context using relevant targets and in close cooperation with two principal end users taking part in the consortium. With their active participation, the ALFA system will make a significant contribution to the development of EUROSUR (in particular, cooperating with SIVE and SIVICC) and be suitable for a range of other missions and scenarios such as homeland and event protection and the protection of critical infrastructure.

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Coastal surveillance systems cannot always give enough warning of aerial threats from small aircraft and drones. ALFA not only detects, identifies and tracks these aerial targets, but also assesses their risk in real time.

Small manned aircraft and drones are increasingly favoured for smuggling illicit items, such as drugs, across borders. Their size and low-flying altitude make detection difficult, and they have ever-increasing reach and load capacities. Additionally, drones can be launched from small, offshore vessels after basic training.
While aerial threats such as these are a global problem, in Europe they have become especially prevalent in the south coast of Portugal and Spain. Yet, conventional coastal surveillance systems, such as radar, are mainly designed to track vessels on the sea’s surface, not airborne vehicles.
The EU-supported ALFA project has pioneered radar technology which detects and classifies Low, Slow and Small (LSS) aerial vehicles. Advanced information processing, including suspicious movements detection or analysis, is under development. This will assess the threat and also predict landing and drop zones, covering significant distances – a first for this type of technology.
The system’s open architecture allows a range of additional sensors, such as LIDAR and acoustic sensors, to be integrated, making it both scalable and responsive to future needs.

Dynamic threat assessment

ALFA built on the successes of the SIVICC Coastal Surveillance System projects and SIVE, for Portugal and Spain respectively. Both demonstrated that a chain of specialist radars could detect sea vessels, almost irrespective of their size or speed.
“These projects showed that virtually no ship could cross a sea border undetected. ALFA grew from the challenge of extending this capability to small, slow-flying aircraft,” says Klaus-Michael Koch, project coordinator.
ALFA is broadly made up of three systems for: detection, analysis and display. Each active radar scanning sensor is designed to detect attributes specific to LSS aircraft. Using rotation signatures, ALFA can discriminate between aerial vehicles that are fixed wing, helicopters or drones. Cameras and time-of-flight technologies determine whether a target is moving or at close range, while also making identification easier. Radio frequency receivers capture the target’s location, along with its wireless communications.
All the information gathered is combined in real time and then classified by the system’s modelling software, prior to suspicious movements detection or analysis which assesses the threat level to be presented to users, on PCs or mobile devices.
The team were able to build their modelling software thanks to knowledge shared by some of the system’s end users – the Guardia Civil in Spain and Portugal’s Guarda Nacional Republicana.

An adaptable system

ALFA’s separate components were individually tested before the integrated system was trialled as a whole, in a dedicated virtual environment. A final demonstration was held in Cacela Velha, Portugal, for 60 representatives from law enforcement agencies and local technicians.
“ALFA was demonstrated to security specialists, and these potential end users validated our unique integrated platform as suitable for their needs,” says Koch.
In June 2019, ALFA was also presented to 20 security force participants from nine EU Member States, at the annual meeting of the European Border and Coast Guard Agency, known as FRONTEX.
As ALFA’s open architecture can exchange data with different systems, it will be interoperable with both SIVE and SIVICC, as well as other systems, such as the French SPATIONAV and the EU EUROSUR system.
ALFA could also protect critical infrastructure (e.g. airports) or large-scale events, so was presented at CETSE, the Spanish Security Technological Centre, last year.
But it isn’t just security applications that can benefit from the new system, it can be adapted to monitor environmental activities such as the seasonal migration of birds.
The team are currently working towards a fully functional prototype as the basis for a commercial product. Once enough data has been added, deep learning and AI algorithms will predict probable landing sites, drop zones and routes. With the right sensor configuration, warning times will also be adjustable by users.

ALFA provides a solution for the detection of small aircraft that are used to smuggle drugs from morocco to Spain and Portugal. The system will assist the policemen to hunt down and arrest the smugglers.

Protecting European borders against drug trafficking is vitally important. More and more, small aircraft are used that can cross the sea border (almost) undetected due to their small size and low flight altitude. A hot-spot in this respect is the Strait of Gibraltar where many cases of airborne drugs smuggling are reported. Drones are already widespread used at the US-Mexican border. It is just a matter of time until drones are used in Europe too. Drones also can be launched from vessels close to the coast.

Efficient pursuit of drug trafficking requires timely warning and knowledge of the intended landing site or dropping zone. This will allow law enforcement entities to intercept the drugs and smugglers on the ground, as well as the pilot in case of landing.

Timely warning cannot always be obtained from existing coastal surveillance systems. Aircraft are small and often low-flying, which makes them hardly visible. Trafficking aircraft typically fly at very low altitudes to avoid showing up on radar during night-time hours or at dawn. Existing radar systems are mainly designed for surface surveillance, in other words for detecting and tracking vessels of all kinds. A system is needed that can add the capability to detect small low flying aircraft and drones. To be able to hunt down and arrest smugglers on the ground, a prediction of the landing or dropping zone is needed.

The ALFA project is developing a system that can cope with the above mentioned situation. The ALFA system consists of radars, cameras and other sensors that are specifically designed to detect small aircraft and drones. Moreover, the system can reveal much information about the craft, like for example the rotational speed of the engine and, for a drone, the number of rotors. This all helps the identification of the drone or aircraft.The following ground breaking objectives are paramount for ALFA:• New radar technologies.Radar is the basis for the system. Existing radar is optimized for the specific task of detecting the Low Slow and Small (LSS) targets in a maritime border environment. An essential part is adding new technologies like micro-Doppler for detecting and classifying LSS targets and making the solution future-proof. • Advanced processing technologies.ALFA’s extensive data fusion and information analysis (including behavioral analysis) is new in its ability to predict landing sites and dropping zones. Moreover it allows the overall objective to be met, which is not possible for a single sensor solution.• Future sensor technologiesALFA’s additional RF sensor solutions (which are passive radar and RF radio-localization system) are for the first time used for maritime border surveillance for larger distances. They will also add to the capability for future evolution of the ALFA system.• Advanced architectural designA new open architecture will be developed that allows any number of relevant heterogeneous sensors to be connected. This makes the ALFA a scalable and flexible system, thereby enabling implementation of future developments.

The work performed in the considered period:• An extensive study has been performed to the type of aircraft that could fulfil the smugglers needs. The inventory encompasses relevant fixed wing, helicopter and UAVs.• Visits have been made to GC and GNR to obtain a good view on the operational aspects of the combatting of drug trafficking. Their requirements with respect to detection of drug trafficking have been discussed. • The architecture design has been detailed, including sensors and processing, information flow and data model, and provisions for connection with other systems (SIVE, SIVICC)• Radar technology has been developed that enable radar to detect small aircraft in a sea clutter environment. The development of specific microDoppler technology for ALFA allows for the extraction of various attributes of the drone or aircraft.• Software is being developed for data fusion, detection, classification, tracking, feature extraction, behavioural analysis, threat analysis and landing site prediction.• Tests have already been performed with the SQUIRE radar and the passive RF system.• First steps have been made in the preparation of the final demonstration.

Progress beyond state-of-the-art and expected results: ALFA will take detection and tracking of low flying, small and/or slow aircraft to a new level. Sensor performance, fusion and processing will be brought to a level that enables superb detection and tracking of targets while providing a good prediction of the most probable landing sites. ALFA will combine four essential steps to resolve this:• Apply highly innovative fusion techniques, to achieve detection and tracking performance that is unachievable for single sensors. It will enable very low false alarm rates, being essential for the system to be of real use to the end-user.• Apply highly innovative classification techniques, essential to separate targets from all clutter which will also be detected when severely lowering detection thresholds in order to detect also smaller and slower targets. These techniques are not in use with current operational systems, but within the consortium, partners have been conducting basic research on these techniques and are ready to make the next step for fielding these techniques.• Apply highly sensitive sensors capable to detect also the smaller and slower air targets. We aim at augmentation of radar by adding new technologies like micro-Doppler (aiming at high TRL) as well as on more exotic sensor solutions (ensuring future evolution).• Inclusion of any available information source. The concepts of open architecture and common data model are known but not exploited yet to the level needed in ALFA, with respect to data rate, heterogeneous data types and application.

Impacts:• ALFA will contribute to development and enhancement of the existing EU surveillance system EUROSUR and prevent cross border crimes:• ALFA detection capability of UAV will be adaptable in other scenarios, not only in the border surveillance (e.g. protection of sensitive infrastructure) and to detect several small targets (e.g. birds), allowing the use of this technology in several other purposes (e.g. monitoring of birds seasonal migration)• ALFA will improve the situational awareness thanks to a continuous detection of targets currently undetectable by many of existing surveillance systems• ALFA will improve the reaction capability and decision making thanks to the early menace detection, to the potential landing sites identification and to the use of tools that are easily deployable and able to increase the surveillance capabilities• ALFA will have positive impacts on user operational procedures and will help in cost reduction, automating surveillance tasks, currently done by using specific resources (helicopters, land patrol and people), that could be employed in other services

Deliverables

will constitute a guideline for communication of the ALFA project to internal and external target groups including conferences, marketing measures and communication channels as well as a description of the official project website hosted by ATOS.

that the ALFA team volunteers to prepare as an early deliverable within the first six months of the project. The purpose of the DMP will be to provide an analysis of the main elements of the data management policy that will be used by the applications with regard to all the datasets that will be generated by the project.

will address the main achievements and concrete key outcomes of the second project year (project summary, work performed and main results, risk assessment, list of scientific publications and dissemination activities).